My question is a bit 'general' and I would be very grateful for any advice. I have data from a GWAS on unrelated Western European patients with a sporadic disease. Is these a 'gold standard' way of dealing with population stratification/substructure/ancestry in the GWAS QC/analysis? If not, there a leading or widely used and accepted way of dealing with this? The way I have done this in the past is to use eigensoft/smartpca to build a principal component model using HapMap genotype data from Europe (CEU), Asia (CHB + JPT) and Africa (YRI), then clustering my samples alongside the HapMap samples and excluding outliers 'by eye'. I'm sure there will be better approaches available. Could people please suggest any approaches. If someone could direct me to an online step-by-step tutorial, if available, that would be much appreciated!
Nasir
You should try STRUCTURE (http://pritch.bsd.uchicago.edu/structure.html). I prefer their graphical output and you get an output file with the percentage of each ancestral population for each individual.
Yes, we used STRUCTURE for our analysis of a Puerto Rican population.